#' print n random rows of a data frame
#'
#' @param df a data frame.
#' @param n number of rows to print. Default = 5
#' @return \code{n} random rows of \code{df}.
#' @examples
#' mid(iris)
#' mid(iris, 10)
#' @export
mid <- function(df,n=5) {
return(df[sample(nrow(df),n),])
}
#' round a number to nearest given integer
#'
#' @param x numeric value, can be a vector.
#' @param base integer to round to. Default = 10
#' @return \code{x} rounded to nearest \code{base}.
#' @examples
#' mround(11.32)
#' mround(seq(1,10,by=0.5),2)
#' @export
mround <- function(x,base=10){
base*round(x/base)
}
#' Calculate root mean square error
#'
#' @param x a single value or vector of observed (reference) values
#' @param y a single value of vector of the same length as \code{x} of predicted values
#' @return root meas square error
#' @examples
#' rmse(x,y)
#' @export
rmse <- function(x,y) {
sqrt(mean((x - y)^2, na.rm = TRUE))
}
#' Calculate most frequent value of a vector
#'
#' @param x a vector
#' @return mode value of \code{x}
#' @examples
#' mode(rnorm(20))
#' @export
mode <- function(x) {
if(is.numeric(x)) {
x <- round(x,2)
}
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]
}
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